Wave attenuation is a central process in the mechanics of a healthy salt marsh. Understanding how wave attenuation varies with vegetation and hydrodynamic conditions informs models of other marsh processes that are a function of wave energy (e.g. sediment transport) and allows for the incorporation of marshes into coastal protection plans. Here, we examine the evolution of wave height across a tidal salt marsh in San Francisco Bay. Instruments were deployed along a cross-shore transect, starting on the mudflat and crossing through zones dominated by Spartina foliosa and Salicornia pacifica. This dataset is the first to quantify wave attenuation for these vegetation species, which are abundant in the intertidal zone of California estuaries. Measurements were collected in the summer and winter to assess seasonal variation in wave attenuation. Calculated drag coefficients of S. foliosa and S. pacifica were similar, indicating equal amounts of vegetation would lead to similar energy dissipation; however, S. pacifica has much greater biomass close to the bed (<20 cm) and retains biomass throughout the year, and therefore, it causes more total attenuation. S. foliosa dies back in the winter, and waves often grow across this section of the marsh. For both vegetation types, attenuation was greatest for low water depths, when the vegetation was emergent. For both seasons, attenuation rates across S. pacifica were the highest and were greater than published attenuation rates across similar (Spartina alterniflora) salt marshes for the comparable depths. These results can inform designs for marsh restorations and management plans in San Francisco Bay and other estuaries containing these species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2018.02.001","usgsCitation":"Foster-Martinez, M.R., Lacy, J.R., Ferner, M.C., and Variano, E., 2018, Wave attenuation across a tidal marsh in San Francisco Bay: Coastal Engineering, v. 136, p. 26-40, https://doi.org/10.1016/j.coastaleng.2018.02.001.","productDescription":"15 p.","startPage":"26","endPage":"40","ipdsId":"IP-090999","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468882,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2018.02.001","text":"Publisher Index Page"},{"id":353003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.50717163085938,\n 38.00049145082287\n ],\n [\n -122.44949340820312,\n 38.00049145082287\n ],\n [\n -122.44949340820312,\n 38.03132654864846\n ],\n [\n -122.50717163085938,\n 38.03132654864846\n ],\n [\n -122.50717163085938,\n 38.00049145082287\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"136","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6f5e4b0da30c1bfbfb3","contributors":{"authors":[{"text":"Foster-Martinez, Madeline R.","contributorId":201705,"corporation":false,"usgs":false,"family":"Foster-Martinez","given":"Madeline","email":"","middleInitial":"R.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":731210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":731209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferner, Matthew C.","contributorId":176972,"corporation":false,"usgs":false,"family":"Ferner","given":"Matthew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":731211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Variano, Evan A.","contributorId":67793,"corporation":false,"usgs":true,"family":"Variano","given":"Evan A.","affiliations":[],"preferred":false,"id":731212,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211579,"text":"70211579 - 2018 - Risk factors associated with mortality of age-0 Smallmouth Bass in the Susquehanna River basin, Pennsylvania","interactions":[],"lastModifiedDate":"2020-07-31T15:23:15.144007","indexId":"70211579","displayToPublicDate":"2018-03-29T08:50:45","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2177,"text":"Journal of Aquatic Animal Health","active":true,"publicationSubtype":{"id":10}},"title":"Risk factors associated with mortality of age-0 Smallmouth Bass in the Susquehanna River basin, Pennsylvania","docAbstract":"Evidence of disease and mortalities of young of the year (age‐0) Smallmouth Bass Micropterus dolomieu has occurred during the late spring and summer in many parts of the Susquehanna River watershed since 2005. To better understand contributing factors, fish collected from multiple areas throughout the watershed as well as out‐of‐basin reference populations (Allegheny and Delaware River basins; experimental ponds, Kearneysville, West Virginia) were examined grossly and histologically for abnormalities. Tissue contaminant concentrations were determined from whole‐body homogenates, and water contaminant concentrations were estimated using time‐integrated passive samplers at selected sites. Observed or isolated pathogens included bacteria, predominantly motile Aeromonas spp. and Flavobacterium columnare ; largemouth bass virus, and parasites, including trematode metacercariae, cestodes, and the myxozoan Myxobolus inornatus . Although these pathogens were found in age‐0 Smallmouth Bass from multiple sites, no one pathogen was consistently associated with mortality. Chemicals detected in tissue included polychlorinated biphenyl (PCB) congeners, organochlorine, and current‐use pesticides. Pyraclostrobin, PCB congeners 170 and 187, cis‐chlordane and trans‐nonachlor were detected in all Susquehanna watershed samples but rarely in samples from the reference site. The findings support the idea that there is no single cause for disease of age‐0 Smallmouth Bass; rather the cumulative effects of co‐infections and potential immunomodulation by environmental stressors during a sensitive developmental life stage may lead to mortality. Identifying the most important risk factors will be necessary for more in‐depth analyses of individual stressors and better management of the habitat and fish populations.
","language":"English","publisher":"Wiley","doi":"10.1002/aah.10009","usgsCitation":"Walsh, H.L., Blazer, V., Smith, G., Lookenbill, M., Alvarez, D.A., and Smalling, K., 2018, Risk factors associated with mortality of age-0 Smallmouth Bass in the Susquehanna River basin, Pennsylvania: Journal of Aquatic Animal Health, v. 30, no. 1, p. 65-80, https://doi.org/10.1002/aah.10009.","productDescription":"16 p.","startPage":"65","endPage":"80","ipdsId":"IP-088555","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":468883,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/aah.10009","text":"Publisher Index Page"},{"id":376952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Susquehanna River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.475341796875,\n 39.74943369178247\n ],\n [\n -75.443115234375,\n 39.74943369178247\n ],\n [\n -75.443115234375,\n 41.95131994679697\n ],\n [\n -78.475341796875,\n 41.95131994679697\n ],\n [\n -78.475341796875,\n 39.74943369178247\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Heather L. 0000-0001-6392-4604","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":213348,"corporation":false,"usgs":false,"family":"Walsh","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":794683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Geoffrey","contributorId":199064,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey","affiliations":[],"preferred":false,"id":794685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lookenbill, Michael 0000-0001-5857-8276","orcid":"https://orcid.org/0000-0001-5857-8276","contributorId":236910,"corporation":false,"usgs":false,"family":"Lookenbill","given":"Michael","email":"","affiliations":[{"id":17703,"text":"Pennsylvania Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":794686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alvarez, David A. 0000-0002-6918-2709","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":220763,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":794687,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794688,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202375,"text":"70202375 - 2018 - A consistent global approach for the morphometric characterization of subaqueous landslides","interactions":[],"lastModifiedDate":"2019-03-01T13:25:29","indexId":"70202375","displayToPublicDate":"2018-03-28T13:25:17","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"A consistent global approach for the morphometric characterization of subaqueous landslides","docAbstract":"Landslides are common in aquatic settings worldwide, from lakes and coastal environments to the deep sea. Fast-moving, large-volume landslides can potentially trigger destructive tsunamis. Landslides damage and disrupt global communication links and other critical marine infrastructure. Landslide deposits act as foci for localized, but important, deep-seafloor biological communities. Under burial, landslide deposits play an important role in a successful petroleum system. While the broad importance of understanding subaqueous landslide processes is evident, a number of important scientific questions have yet to receive the needed attention. Collecting quantitative data is a critical step to addressing questions surrounding subaqueous landslides.
Quantitative metrics of subaqueous landslides are routinely recorded, but which ones, and how they are defined, depends on the end-user focus. Differences in focus can inhibit communication of knowledge between communities, and complicate comparative analysis. This study outlines an approach specifically for consistent measurement of subaqueous landslide morphometrics to be used in the design of a broader, global open-source, peer-curated database. Examples from different settings illustrate how the approach can be applied, as well as the difficulties encountered when analysing different landslides and data types. Standardizing data collection for subaqueous landslides should result in more accurate geohazard predictions and resource estimation.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/SP477.15","usgsCitation":"Clare, M., Chaytor, J., Dabson, O., Gamboa, D., Georgiopoulou, A., Eady, H., Hunt, J., Jackson, C., Katz, O., Krastel, S., Leon, R., Micallef, A., Moernaut, J., Moriconi, R., Moscardelli, L., Mueller, C., Normandeau, A., Patacci, M., Steventon, M., Urlaub, M., Volker, D., Wood, L., and Jobe, Z.R., 2018, A consistent global approach for the morphometric characterization of subaqueous landslides: Geological Society, London, Special Publications, v. 477, 23 p., https://doi.org/10.1144/SP477.15.","productDescription":"23 p.","ipdsId":"IP-090342","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/sp477.15","text":"Publisher Index Page"},{"id":361649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"477","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Clare, Michael","contributorId":213585,"corporation":false,"usgs":false,"family":"Clare","given":"Michael","email":"","affiliations":[{"id":38805,"text":"National Oceanography Centre, University of Southampton Waterfront Campus, European Way, Southampton, SO14 3ZH, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":758069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":758068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dabson, Oliver","contributorId":213586,"corporation":false,"usgs":false,"family":"Dabson","given":"Oliver","email":"","affiliations":[{"id":38806,"text":"CH2M, Elms House, 43 Brook Green, London W6 7EF, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":758070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gamboa, Davide","contributorId":213587,"corporation":false,"usgs":false,"family":"Gamboa","given":"Davide","email":"","affiliations":[{"id":38807,"text":"British Geological Survey, Room 0.73 Cardiff University Main Building, Cardiff CF110 3AT, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":758071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Georgiopoulou, Aggeliki","contributorId":213588,"corporation":false,"usgs":false,"family":"Georgiopoulou","given":"Aggeliki","email":"","affiliations":[{"id":38808,"text":"UCD School of Earth Sciences, University College Dublin, Dublin, Ireland","active":true,"usgs":false}],"preferred":false,"id":758072,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eady, Harry","contributorId":213589,"corporation":false,"usgs":false,"family":"Eady","given":"Harry","email":"","affiliations":[{"id":38809,"text":"Fugro GeoServices Limited, Fugro House, Hithercroft Road, Wallingford, Oxfordshire OX10 9RB","active":true,"usgs":false}],"preferred":false,"id":758073,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hunt, James","contributorId":213884,"corporation":false,"usgs":false,"family":"Hunt","given":"James","affiliations":[],"preferred":false,"id":758074,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jackson, Christopher","contributorId":213885,"corporation":false,"usgs":false,"family":"Jackson","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":758075,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Katz, Oded","contributorId":213590,"corporation":false,"usgs":false,"family":"Katz","given":"Oded","email":"","affiliations":[{"id":38810,"text":"Geological Survey of Israel, Jerusalem, Israel","active":true,"usgs":false}],"preferred":false,"id":758076,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Krastel, Sebastian","contributorId":175295,"corporation":false,"usgs":false,"family":"Krastel","given":"Sebastian","email":"","affiliations":[],"preferred":false,"id":758077,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Leon, Ricardo","contributorId":213591,"corporation":false,"usgs":false,"family":"Leon","given":"Ricardo","email":"","affiliations":[{"id":38811,"text":"IGME, Geological Survey of Spain, 28003 Madrid, Spain","active":true,"usgs":false}],"preferred":false,"id":758078,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Micallef, Aaron","contributorId":175297,"corporation":false,"usgs":false,"family":"Micallef","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":758079,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Moernaut, Jasper","contributorId":194084,"corporation":false,"usgs":false,"family":"Moernaut","given":"Jasper","email":"","affiliations":[],"preferred":false,"id":758080,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Moriconi, Roberto","contributorId":213592,"corporation":false,"usgs":false,"family":"Moriconi","given":"Roberto","email":"","affiliations":[{"id":38812,"text":"Formerly Fugro Oceansismica S.P.A., 268 Viale Lenormant Charles, Roma, RM 00126, Italy","active":true,"usgs":false}],"preferred":false,"id":758081,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Moscardelli, Lorena","contributorId":147083,"corporation":false,"usgs":false,"family":"Moscardelli","given":"Lorena","email":"","affiliations":[],"preferred":false,"id":758082,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Mueller, Christof","contributorId":175298,"corporation":false,"usgs":false,"family":"Mueller","given":"Christof","email":"","affiliations":[{"id":36364,"text":"Institute of Geological and Nuclear Sciences (GNS), Lower Hutt, New Zealand","active":true,"usgs":false}],"preferred":false,"id":758083,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Normandeau, Alexandre","contributorId":213593,"corporation":false,"usgs":false,"family":"Normandeau","given":"Alexandre","email":"","affiliations":[{"id":38813,"text":"Geological Survey of Canada - Atlantic, Bedford Institute of Oceanography, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":758084,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Patacci, Marco","contributorId":213594,"corporation":false,"usgs":false,"family":"Patacci","given":"Marco","email":"","affiliations":[{"id":38814,"text":"Institute of Applied Geoscience, School of Earth and Environment, University of Leeds, Leeds LS2 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David","contributorId":213597,"corporation":false,"usgs":false,"family":"Volker","given":"David","email":"","affiliations":[{"id":38817,"text":"David Völker, Marum - Zentrum für Marine Umweltwissenschaften, der Universität Bremen, Postfach 330 440, 28334, Bremen","active":true,"usgs":false}],"preferred":false,"id":758088,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Wood, Lesli","contributorId":213886,"corporation":false,"usgs":false,"family":"Wood","given":"Lesli","email":"","affiliations":[],"preferred":false,"id":758089,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Jobe, Zane R.","contributorId":207547,"corporation":false,"usgs":false,"family":"Jobe","given":"Zane","email":"","middleInitial":"R.","affiliations":[{"id":37560,"text":"Department of Geology and Geological Engineering, Colorado School of Mines, Golden, Colorado 80401, USA","active":true,"usgs":false}],"preferred":false,"id":758090,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70216337,"text":"70216337 - 2018 - Hierarchical modeling assessment of the influence of watershed stressors on fish and invertebrate species in Gulf of Mexico estuaries","interactions":[],"lastModifiedDate":"2020-11-12T15:39:40.108738","indexId":"70216337","displayToPublicDate":"2018-03-28T09:35:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical modeling assessment of the influence of watershed stressors on fish and invertebrate species in Gulf of Mexico estuaries","docAbstract":"The northern Gulf of Mexico (GoM) spans five U.S. states and encompasses estuaries that vary greatly in size, shape, upstream river input, eutrophication status, and biotic communities. Given the variability among these estuaries, assessing their biological condition relative to anthropogenic stressors is challenging, but important to regional fisheries management and habitat conservation initiatives. Here, a hierarchical generalized linear modeling approach was developed to predict species presence in bottom trawl samples, using data from 33 estuaries over a nineteen-year study period. This is the first GoM estuary assessment to leverage Gulf-wide trawl data to develop species-level indicators and a quantitative index of estuary disturbance. After controlling for sources of variability at the sampling event, estuary, state, and sampling program levels, our approach screened for statistically significant relationships between watershed-level anthropogenic stressors and fish and invertebrate species presence. Modeling results indicate species level indicators with sensitivities to landscape stressor gradients. The most influential stressors include total anthropogenic land use, crop land use, and the number of toxic release sites in upstream watersheds, as well as agriculture in the shoreline buffer, each of which was significantly related to between 21% and 39% of the 57 species studied. Averaging the effects of these influential stressors across species, we develop a quantitative estuary stress index that can be compared against benchmark conditions. In general, disturbance levels were greatest in estuaries west of the Mississippi delta and in highly developed estuaries in southwest Florida. Estuaries from the Florida panhandle to the eastern Mississippi delta had less anthropogenic stress.
Habitat models using lidar-derived variables that quantify fine-scale variation in vegetation structure can improve the accuracy of occupancy estimates for canopy-dwelling species over models that use variables derived from other remote sensing techniques. However, the ability of models developed at such a fine spatial scale to maintain accuracy at regional or larger spatial scales has not been tested. We tested the transferability of a lidar-based habitat model for the threatened Marbled Murrelet (Brachyramphus marmoratus) between two management districts within a larger regional conservation zone in coastal western Oregon. We compared the performance of the transferred model against models developed with data from the application location. The transferred model had good discrimination (AUC = 0.73) at the application location, and model performance was further improved by fitting the original model with coefficients from the application location dataset (AUC = 0.79). However, the model selection procedure indicated that neither of these transferred models were considered competitive with a model trained on local data. The new model trained on data from the application location resulted in the selection of a slightly different set of lidar metrics from the original model, but both transferred and locally trained models consistently indicated positive relationships between the probability of occupancy and lidar measures of canopy structural complexity. We conclude that while the locally trained model had superior performance for local application, the transferred model could reasonably be applied to the entire conservation zone.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181035","usgsCitation":"Hagar, J.C., Perez, R.A., Haggerty, P., and Hollenbeck, J.P., 2018, Modeling habitat for Marbled Murrelets on the Siuslaw National Forest, Oregon, using lidar data: U.S. Geological Survey Open-File Report 2018–1035, 21 p., https://doi.org/10.3133/ofr20181035.","productDescription":"iv, 21 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-088393","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":352857,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1035/ofr20181035.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1035"},{"id":352856,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1035/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Siuslaw National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.68383789062499,\n 41.9921602333763\n ],\n [\n -123.28857421875,\n 41.9921602333763\n ],\n [\n -123.28857421875,\n 45.62172169252446\n ],\n [\n -124.68383789062499,\n 45.62172169252446\n ],\n [\n -124.68383789062499,\n 41.9921602333763\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
We conducted a large-scale assessment of unconventional oil and gas (UOG) development effects on brook trout (Salvelinus fontinalis) distribution. We compiled 2231 brook trout collection records from the Upper Susquehanna River Watershed, USA. We used boosted regression tree (BRT) analysis to predict occurrence probability at the 1:24,000 stream-segment scale as a function of natural and anthropogenic landscape and climatic attributes. We then evaluated the importance of landscape context (i.e., pre-existing natural habitat quality and anthropogenic degradation) in modulating the effects of UOG on brook trout distribution under UOG development scenarios. BRT made use of 5 anthropogenic (28% relative influence) and 7 natural (72% relative influence) variables to model occurrence with a high degree of accuracy [Area Under the Receiver Operating Curve (AUC) = 0.85 and cross-validated AUC = 0.81]. UOG development impacted 11% (n = 2784) of streams and resulted in a loss of predicted occurrence in 126 (4%). Most streams impacted by UOG had unsuitable underlying natural habitat quality (n = 1220; 44%). Brook trout were predicted to be absent from an additional 26% (n = 733) of streams due to pre-existing non-UOG land uses (i.e., agriculture, residential and commercial development, or historic mining). Streams with a predicted and observed (via existing pre- and post-disturbance fish sampling records) loss of occurrence due to UOG tended to have intermediate natural habitat quality and/or intermediate levels of non-UOG stress. Simulated development of permitted but undeveloped UOG wells (n = 943) resulted in a loss of predicted occurrence in 27 additional streams. Loss of occurrence was strongly dependent upon landscape context, suggesting effects of current and future UOG development are likely most relevant in streams near the probability threshold due to pre-existing habitat degradation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.02.062","usgsCitation":"Merriam, E.R., Petty, J.T., Maloney, K.O., Young, J.A., Faulkner, S., Slonecker, E.T., Milheim, L., Hailegiorgis, A., and Niles, J.M., 2018, Brook trout distributional response to unconventional oil and gas development: Landscape context matters: Science of the Total Environment, v. 628-629, p. 338-349, https://doi.org/10.1016/j.scitotenv.2018.02.062.","productDescription":"12 p.","startPage":"338","endPage":"349","ipdsId":"IP-093043","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":468888,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.02.062","text":"Publisher Index Page"},{"id":352823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, Pennsylvania","otherGeospatial":"Upper Susquehanna River Watershed","volume":"628-629","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6f6e4b0da30c1bfbfbd","contributors":{"authors":[{"text":"Merriam, Eric R.","contributorId":203597,"corporation":false,"usgs":false,"family":"Merriam","given":"Eric","email":"","middleInitial":"R.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":731842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petty, J. Todd","contributorId":166749,"corporation":false,"usgs":false,"family":"Petty","given":"J.","email":"","middleInitial":"Todd","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":731843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":731841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":731844,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Faulkner, Stephen 0000-0001-5295-1383 faulkners@usgs.gov","orcid":"https://orcid.org/0000-0001-5295-1383","contributorId":146152,"corporation":false,"usgs":true,"family":"Faulkner","given":"Stephen","email":"faulkners@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":731845,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Slonecker, E. Terrence 0000-0002-5793-0503 tslonecker@usgs.gov","orcid":"https://orcid.org/0000-0002-5793-0503","contributorId":168591,"corporation":false,"usgs":true,"family":"Slonecker","given":"E.","email":"tslonecker@usgs.gov","middleInitial":"Terrence","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"preferred":true,"id":731846,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Milheim, Lesley E. lmilheim@usgs.gov","contributorId":2560,"corporation":false,"usgs":true,"family":"Milheim","given":"Lesley E.","email":"lmilheim@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":731847,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hailegiorgis, Atesmachew","contributorId":196129,"corporation":false,"usgs":false,"family":"Hailegiorgis","given":"Atesmachew","email":"","affiliations":[],"preferred":false,"id":731848,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Niles, Jonathan M.","contributorId":146975,"corporation":false,"usgs":false,"family":"Niles","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[{"id":35657,"text":"Susquehanna University, Selinsgrove, PA","active":true,"usgs":false}],"preferred":false,"id":731849,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70196256,"text":"70196256 - 2018 - Microspatial ecotone dynamics at a shifting range limit: plant–soil variation across salt marsh–mangrove interfaces","interactions":[],"lastModifiedDate":"2018-05-14T13:13:06","indexId":"70196256","displayToPublicDate":"2018-03-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Microspatial ecotone dynamics at a shifting range limit: plant–soil variation across salt marsh–mangrove interfaces","docAbstract":"Ecotone dynamics and shifting range limits can be used to advance our understanding of the ecological implications of future range expansions in response to climate change. In the northern Gulf of Mexico, the salt marsh–mangrove ecotone is an area where range limits and ecotone dynamics can be studied in tandem as recent decreases in winter temperature extremes have allowed for mangrove expansion at the expense of salt marsh. In this study, we assessed aboveground and belowground plant–soil dynamics across the salt marsh–mangrove ecotone quantifying micro-spatial patterns in horizontal extent. Specifically, we studied vegetation and rooting dynamics of large and small trees, the impact of salt marshes (e.g. species and structure) on mangroves, and the influence of vegetation on soil properties along transects from underneath the mangrove canopy into the surrounding salt marsh. Vegetation and rooting dynamics differed in horizontal reach, and there was a positive relationship between mangrove tree height and rooting extent. We found that the horizontal expansion of mangrove roots into salt marsh extended up to eight meters beyond the aboveground boundary. Variation in vegetation structure and local hydrology appear to control mangrove seedling dynamics. Finally, soil carbon density and organic matter did not differ within locations across the salt marsh-mangrove interface. By studying aboveground and belowground variation across the ecotone, we can better predict the ecological effects of continued range expansion in response to climate change.
","language":"English","publisher":"Springer","doi":"10.1007/s00442-018-4098-2","usgsCitation":"Yando, E.S., Osland, M.J., and Hester, M.H., 2018, Microspatial ecotone dynamics at a shifting range limit: plant–soil variation across salt marsh–mangrove interfaces: Oecologia, v. 187, no. 1, p. 319-331, https://doi.org/10.1007/s00442-018-4098-2.","productDescription":"13 p.","startPage":"319","endPage":"331","ipdsId":"IP-091178","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":352849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"187","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-01","publicationStatus":"PW","scienceBaseUri":"5afee6f5e4b0da30c1bfbfbb","contributors":{"authors":[{"text":"Yando, Erik S.","contributorId":127788,"corporation":false,"usgs":false,"family":"Yando","given":"Erik","email":"","middleInitial":"S.","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":731898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":731897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hester, Mark H.","contributorId":203609,"corporation":false,"usgs":false,"family":"Hester","given":"Mark","email":"","middleInitial":"H.","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":731899,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195368,"text":"70195368 - 2018 - Spatiotemporal heterogeneity in prey abundance and vulnerability shapes the foraging tactics of an omnivore","interactions":[],"lastModifiedDate":"2018-04-17T12:20:30","indexId":"70195368","displayToPublicDate":"2018-03-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal heterogeneity in prey abundance and vulnerability shapes the foraging tactics of an omnivore","docAbstract":"Communities are faced with the challenge of meeting regulatory requirements mandating reductions in water pollution from stormwater and combined sewer overflows (CSO). Green stormwater infrastructure and gray stormwater infrastructure are two types of water management strategies communities can use to address water pollution. In this study, we used long-term control plans from 25 U.S. cities to synthesize: the types of gray and green infrastructure being used by communities to address combined sewer overflows; the types of goals set; biophysical characteristics of each city; and factors associated with the governance of stormwater management. These city characteristics were then used to identify common characteristics of “green leader” cities—those that dedicated >20% of the control plan budget in green infrastructure. Five “green leader” cities were identified: Milwaukee, WI, Philadelphia, PA, Syracuse, NY, New York City, NY, and Buffalo, NY. These five cities had explicit green infrastructure goals targeting the volume of stormwater or percentage of impervious cover managed by green infrastructure. Results suggested that the management scale and complexity of the management system are less important factors than the ability to harness a “policy window” to integrate green infrastructure into control plans. Two case studies—Philadelphia, PA, and Milwaukee, WI—indicated that green leader cities have a long history of building momentum for green infrastructure through a series of phases from experimentation, demonstration, and finally—in the case of Philadelphia—a full transition in the approach used to manage CSOs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsci.2018.03.008","usgsCitation":"Hopkins, K.G., Grimm, N.B., and York, A.M., 2018, Influence of governance structure on green stormwater infrastructure investment: Environmental Science and Policy, v. 84, p. 124-133, https://doi.org/10.1016/j.envsci.2018.03.008.","productDescription":"10 p.","startPage":"124","endPage":"133","ipdsId":"IP-093747","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":468886,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsci.2018.03.008","text":"Publisher Index Page"},{"id":352822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6f6e4b0da30c1bfbfbf","contributors":{"authors":[{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":731838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grimm, Nancy B.","contributorId":44058,"corporation":false,"usgs":false,"family":"Grimm","given":"Nancy","email":"","middleInitial":"B.","affiliations":[{"id":24511,"text":"Arizona State University, Tempe AZ USA 85287","active":true,"usgs":false}],"preferred":false,"id":731839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"York, Abigail M.","contributorId":203596,"corporation":false,"usgs":false,"family":"York","given":"Abigail","email":"","middleInitial":"M.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":731840,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191637,"text":"70191637 - 2018 - Research frontiers for improving our understanding of drought‐induced tree and forest mortality","interactions":[],"lastModifiedDate":"2018-03-28T15:28:56","indexId":"70191637","displayToPublicDate":"2018-03-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Research frontiers for improving our understanding of drought‐induced tree and forest mortality","docAbstract":"Accumulating evidence highlights increased mortality risks for trees during severe drought, particularly under warmer temperatures and increasing vapour pressure deficit (VPD). Resulting forest die‐off events have severe consequences for ecosystem services, biophysical and biogeochemical land–atmosphere processes. Despite advances in monitoring, modelling and experimental studies of the causes and consequences of tree death from individual tree to ecosystem and global scale, a general mechanistic understanding and realistic predictions of drought mortality under future climate conditions are still lacking. We update a global tree mortality map and present a roadmap to a more holistic understanding of forest mortality across scales. We highlight priority research frontiers that promote: (1) new avenues for research on key tree ecophysiological responses to drought; (2) scaling from the tree/plot level to the ecosystem and region; (3) improvements of mortality risk predictions based on both empirical and mechanistic insights; and (4) a global monitoring network of forest mortality. In light of recent and anticipated large forest die‐off events such a research agenda is timely and needed to achieve scientific understanding for realistic predictions of drought‐induced tree mortality. The implementation of a sustainable network will require support by stakeholders and political authorities at the international level.
","language":"English","publisher":"New Phytologist Trust","doi":"10.1111/nph.15048","usgsCitation":"Hartmann, H., Moura, C., Anderegg, W.R., Ruehr, N.K., Salmon, Y., Allen, C.D., Arndt, S.K., Breshears, D.D., Davi, H., Galbraith, D., Ruthrof, K.X., Wunder, J., Adams, H., Bloemen, J., Cailleret, M., Cobb, R., Gessler, A., Grams, T.E., Jansen, S., Kautz, M., Lloret, F., and O’Brien, M., 2018, Research frontiers for improving our understanding of drought‐induced tree and forest mortality: New Phytologist, v. 218, no. 1, p. 15-28, https://doi.org/10.1111/nph.15048.","productDescription":"14 p.","startPage":"15","endPage":"28","ipdsId":"IP-079836","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468887,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.15048","text":"Publisher Index Page"},{"id":352874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"218","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee6f6e4b0da30c1bfbfc7","contributors":{"authors":[{"text":"Hartmann, Henrik","contributorId":181974,"corporation":false,"usgs":false,"family":"Hartmann","given":"Henrik","email":"","affiliations":[],"preferred":false,"id":731945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moura, Catarina","contributorId":197207,"corporation":false,"usgs":false,"family":"Moura","given":"Catarina","email":"","affiliations":[],"preferred":false,"id":731946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderegg, William R. L.","contributorId":166785,"corporation":false,"usgs":false,"family":"Anderegg","given":"William","email":"","middleInitial":"R. L.","affiliations":[{"id":24514,"text":"Department of Ecology and Evolutionary Biology, Princeton University, Princeton NJ 08544","active":true,"usgs":false}],"preferred":false,"id":731947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruehr, Nadine K.","contributorId":197208,"corporation":false,"usgs":false,"family":"Ruehr","given":"Nadine","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":731948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Salmon, Yann","contributorId":197209,"corporation":false,"usgs":false,"family":"Salmon","given":"Yann","email":"","affiliations":[],"preferred":false,"id":731949,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":731950,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arndt, Stefan K.","contributorId":203621,"corporation":false,"usgs":false,"family":"Arndt","given":"Stefan","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":731951,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Breshears, David D.","contributorId":51620,"corporation":false,"usgs":false,"family":"Breshears","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":731952,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Davi, Hendrik","contributorId":181968,"corporation":false,"usgs":false,"family":"Davi","given":"Hendrik","email":"","affiliations":[],"preferred":false,"id":731953,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Galbraith, David","contributorId":19479,"corporation":false,"usgs":true,"family":"Galbraith","given":"David","affiliations":[],"preferred":false,"id":731954,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ruthrof, Katinka X.","contributorId":203622,"corporation":false,"usgs":false,"family":"Ruthrof","given":"Katinka","email":"","middleInitial":"X.","affiliations":[],"preferred":false,"id":731955,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wunder, Jan","contributorId":203623,"corporation":false,"usgs":false,"family":"Wunder","given":"Jan","email":"","affiliations":[],"preferred":false,"id":731956,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Adams, Henry D.","contributorId":105619,"corporation":false,"usgs":true,"family":"Adams","given":"Henry D.","affiliations":[],"preferred":false,"id":731957,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bloemen, Jasper","contributorId":203624,"corporation":false,"usgs":false,"family":"Bloemen","given":"Jasper","email":"","affiliations":[],"preferred":false,"id":731958,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Cailleret, Maxime 0000-0001-6561-1943","orcid":"https://orcid.org/0000-0001-6561-1943","contributorId":181952,"corporation":false,"usgs":false,"family":"Cailleret","given":"Maxime","email":"","affiliations":[],"preferred":false,"id":731959,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Cobb, Richard","contributorId":203625,"corporation":false,"usgs":false,"family":"Cobb","given":"Richard","affiliations":[],"preferred":false,"id":731960,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Gessler, Arthur","contributorId":199448,"corporation":false,"usgs":false,"family":"Gessler","given":"Arthur","email":"","affiliations":[],"preferred":false,"id":731961,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Grams, Thorsten E. E.","contributorId":203626,"corporation":false,"usgs":false,"family":"Grams","given":"Thorsten","email":"","middleInitial":"E. E.","affiliations":[],"preferred":false,"id":731962,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Jansen, Steven","contributorId":181953,"corporation":false,"usgs":false,"family":"Jansen","given":"Steven","email":"","affiliations":[],"preferred":false,"id":731963,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Kautz, Markus","contributorId":203627,"corporation":false,"usgs":false,"family":"Kautz","given":"Markus","email":"","affiliations":[],"preferred":false,"id":731964,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Lloret, Francisco","contributorId":181986,"corporation":false,"usgs":false,"family":"Lloret","given":"Francisco","email":"","affiliations":[],"preferred":false,"id":731965,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"O’Brien, Michael","contributorId":199900,"corporation":false,"usgs":false,"family":"O’Brien","given":"Michael","affiliations":[],"preferred":false,"id":731966,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70191014,"text":"sir20175111 - 2018 - Review of the geochemistry and metallogeny of approximately 1.4 Ga granitoid intrusions of the conterminous United States","interactions":[],"lastModifiedDate":"2020-10-05T16:15:21.750634","indexId":"sir20175111","displayToPublicDate":"2018-03-27T15:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5111","title":"Review of the geochemistry and metallogeny of approximately 1.4 Ga granitoid intrusions of the conterminous United States","docAbstract":"The conterminous United States hosts numerous volumetrically significant and geographically dispersed granitoid intrusions that range in age from 1.50 to 1.32 billion years before present (Ga). Although previously referred to as A-type granites, most are better described as ferroan granites. These granitoid intrusions are distributed in the northern and central Rocky Mountains, the Southwest, the northern midcontinent, and a swath largely buried beneath Phanerozoic cover across the Great Plains and into the southern midcontinent. These intrusions, with ages that are bimodally distributed between about 1.455–1.405 Ga and 1.405–1.320 Ga, are dispersed nonsystematically with respect to age across their spatial extents. Globally, although A-type or ferroan granites are genetically associated with rare-metal deposits, most U.S. 1.4 Ga granitoid intrusions do not contain significant deposits. Exceptions are the light rare-earth element deposit at Mountain Pass, California, and the iron oxide-apatite and iron oxide-copper-gold deposits in southeast Missouri.
Most of the U.S. 1.4 Ga granitoid intrusions are composed of hornblende ± biotite or biotite ± muscovite monzogranite, commonly with prominent alkali feldspar megacrysts; however, modal compositions vary widely. These intrusions include six of the eight commonly identified subtypes of ferroan granite: alkali-calcic and calc-alkalic peraluminous subtypes; alkalic, alkali-calcic, and calc-alkalic metaluminous subtypes; and the alkalic peralkaline subtype. The U.S. 1.4 Ga granitoid intrusions also include variants of these subtypes that have weakly magnesian compositions. Extreme large-ion lithophile element enrichments typical of ferroan granites elsewhere are absent among these intrusions. Chondrite-normalized rare-earth element patterns for these intrusions have modest negative slopes and moderately developed negative europium anomalies. Their radiogenic isotopic compositions are consistent with mixing involving primitive, mantle-derived components and evolved, crust-derived components.
Each compositional subtype can be ascribed to a relatively unique petrogenetic history. The numerically dominant ferroan, peraluminous granites probably represent low-degree, relatively high-pressure partial melting of preexisting, crust-derived, intermediate-composition granitoids. The moderately numerous, weakly magnesian, peraluminous granites probably reflect similar partial melting but at a higher degree and in a lower pressure environment. In contrast, the ferroan but metaluminous granites may be the result of extensive differentiation of tholeiitic basalt. Finally, the peralkaline igneous rocks at Mountain Pass have compositions potentially derived by differentiation of alkali basalt. The varying alkalic character of each subtype probably reflects polybaric petrogenesis and the corresponding effect of diverse mineral stabilities on ultimate melt compositions. Mantle-derived mafic magma and variably assimilated partial melts of mainly juvenile Paleoproterozoic crustal components are required to generate the relatively low initial strontium (87Sr/86Sr) and distinctive neodymium isotope compositions characteristic of the U.S. 1.4 Ga granitoid intrusions. The characteristics of these intrusions are consistent with crustal melting in an extensional/decompressional, intracratonic setting that was triggered by mantle upwelling and emplacement of tholeiitic basaltic magma at or near the base of the crust. Composite magmas, formed by mingling and mixing mantle components with partial melts of Paleoproterozoic crust, produced variably homogenized storage reservoirs that continued polybaric evolution as intrusions lodged at various crustal depths.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175111","usgsCitation":"du Bray, E.A., Holm-Denoma, C.S., Lund, Karen, and Premo, W.R., 2018, Review of the geochemistry and metallogeny of approximately 1.4 Ga granitoid intrusions of the conterminous United States: U.S. Geological Survey Scientific Investigations Report 2017–5111, 34 p., https://doi.org/sir20175111.","productDescription":"vi, 34 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-084161","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":352708,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5111/coverthb.jpg"},{"id":352709,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5111/sir20175111.pdf","text":"Report","size":"38.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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\"}}]}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
Hemimysis anomala is a recent invader to North American aquatic ecosystems and is spreading rapidly throughout the Great Lakes region. This is the first littoral mysid in the North American Great Lakes; and, as such, the ecosystem effects are unknown and could be substantial. These effects depend on the role of Hemimysis in the food web and, therefore, on its diet. We examined the stomach contents of two life stages of Hemimysis from two sites in Lake Ontario during the growing season (May–November 2010). We also report the relationship between zooplankton hard parts and size for a number of potential prey species to allow the back-calculation of prey lengths from stomach contents. Both juvenile (2–5 mm) and adult Hemimysis (5–11 mm) were omnivorous, consuming phytoplankton, zooplankton, and benthos when available. However, adults appeared slightly more carnivorous and incorporated larger prey in their diets. Hemimysis were able to consume zooplankton prey up to 30% of their own length, including Bythotrephes longimanus and Cercopagis pengoi. Daphnia and Bosmina were selected over other prey by both juvenile and adult Hemimysis and were most common in stomachs during July and September when their abundances in the zooplankton were highest. Measurements of δ13C and δ15N corroborated stomach content materials, indicating an omnivorous diet which included benthic and pelagic sources. Omnivory by Hemimysis is typical of mysids in general and makes them less sensitive to seasonal dynamics of preferred prey items.
Conservation resources have become increasingly limited and, along with social, cultural and political complexities, this shortfall frequently challenges effectiveness in conservation. Because conservation can be costly, efforts are often only initiated after a species has declined below a critical threshold and/or when statutory protection is mandated. However, implementing conservation proactively, rather than reactively, is predicted to be less costly and to decrease a species' risk of extinction. Despite these benefits, I document that the number of studies that have implemented proactive conservation around the world are far fewer than those that simply acknowledge the need for such action. I provide examples of proactive actions that can ameliorate shortfalls in funding and other assets, thus helping conservation practitioners and managers cope with the constraints that resource limitation imposes. Not all of these options are new; however, the timing of their implementation is critical for effective conservation, and the need for more proactive conservation is increasingly recognized. These actions are (1) strengthening and diversifying stakeholder involvement in conservation projects; (2) complementing time-consuming and labor-intensive demographic studies with alternative approaches of detecting declines and estimating extinction risk; and (3) minimizing future costly conservation and management by proactively keeping common species common. These approaches may not constitute a cure-all for every conservation crisis. However, given escalating rates of species' losses, perhaps a reminder that these proactive actions can reduce conservation costs, save time, and potentially thwart population declines is warranted.
","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2018.00024","usgsCitation":"Walls, S.C., 2018, Coping with constraints: Achieving effective conservation with limited resources: Frontiers in Ecology and Evolution, v. 6, p. 1-8, https://doi.org/10.3389/fevo.2018.00024.","productDescription":"Article 24; 8 p.","startPage":"1","endPage":"8","ipdsId":"IP-093033","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468891,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2018.00024","text":"Publisher Index Page"},{"id":352807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-16","publicationStatus":"PW","scienceBaseUri":"5afee6f6e4b0da30c1bfbfcb","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":731766,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70196220,"text":"70196220 - 2018 - Continuous gravity and tilt reveal anomalous pressure and density changes associated with gas pistoning within the summit lava lake of Kīlauea Volcano, Hawaiʻi","interactions":[],"lastModifiedDate":"2018-03-27T11:45:01","indexId":"70196220","displayToPublicDate":"2018-03-27T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Continuous gravity and tilt reveal anomalous pressure and density changes associated with gas pistoning within the summit lava lake of Kīlauea Volcano, Hawaiʻi","docAbstract":"Gas piston events within the summit eruptive vent of Kīlauea Volcano, Hawai‘i, are characterized by increases in lava level and by decreases in seismic energy release, spattering, and degassing. During 2010–2011, gas piston events were especially well manifested, with lava level rises of tens of meters over the course of several hours, followed by a sudden drop to preevent levels. The changes in lava level were accompanied by directly proportional changes in gravity, but ground deformation determined from tilt was anticorrelative. The small magnitude of the gravity changes, compared to the large changes in volume within the vent during gas pistons, suggests that pistoning involves the accumulation of a very low‐density (100–200 kg/m3) foam at the top of the lava column. Co‐event ground tilt indicates that rise in lava level is paradoxically associated with deflation (the opposite is usually true), which can be modeled as an increase in the gas content of the magma column between the source reservoir and the surface. Gas pistoning behavior is therefore associated with not only accumulation of a shallow magmatic foam but also more bubbles within the feeder conduit, probably due to the overall decrease in gas emissions from the lava lake during piston events.
","language":"English","publisher":"AGU","doi":"10.1002/2017GL076936","usgsCitation":"Poland, M.P., and Carbone, D., 2018, Continuous gravity and tilt reveal anomalous pressure and density changes associated with gas pistoning within the summit lava lake of Kīlauea Volcano, Hawaiʻi: Geophysical Research Letters, v. 45, no. 5, p. 2319-2327, https://doi.org/10.1002/2017GL076936.","productDescription":"9 p.","startPage":"2319","endPage":"2327","ipdsId":"IP-093410","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":352783,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.302734375,\n 19.3869432241507\n ],\n [\n -155.23252487182617,\n 19.3869432241507\n ],\n [\n -155.23252487182617,\n 19.438751897344126\n ],\n [\n -155.302734375,\n 19.438751897344126\n ],\n [\n -155.302734375,\n 19.3869432241507\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5afee6f6e4b0da30c1bfbfcd","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":731734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carbone, Daniele","contributorId":124561,"corporation":false,"usgs":false,"family":"Carbone","given":"Daniele","email":"","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":731735,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195548,"text":"ofr20181012 - 2018 - Decadal changes in channel morphology of a freely meandering river—Powder River, Montana, 1975–2016","interactions":[],"lastModifiedDate":"2018-03-26T15:15:34","indexId":"ofr20181012","displayToPublicDate":"2018-03-26T16:10:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1012","title":"Decadal changes in channel morphology of a freely meandering river—Powder River, Montana, 1975–2016","docAbstract":"Few studies exist on the long-term geomorphic effects of floods. However, the U.S. Geological Survey (USGS) was able to begin such a study after a 50-year recurrence interval flood in 1978 because 20 channel cross sections along a 100-kilometer reach of river were established in 1975 and 1977 as part of a study for a proposed dam on Powder River in southeastern Montana. These cross-section measurements (data for each channel cross section are available at the USGS ScienceBase website) have been repeated about 30 times during four decades (1975–2016) and provide a unique dataset for understanding long-term changes in channel morphology caused by an extreme flood and a spectrum of annual floods.
Changes in channel morphology of a 100-kilometer reach of Powder River are documented in a series of narratives for each channel cross section that include a time series of photographs as a record of these changes. The primary change during the first decade (1975–85) was the rapid vertical growth of a new inset flood plain within the flood-widened channel. Changes during the second decade (1985–95) were characterized by slower growth of the flood plain, and the effects of ice-jam floods typical of a northward-flowing river. Changes during the third decade (1995–2005) showed little vertical growth of the inset flood plain, which had reached a height that limited overbank deposition. And changes during the final decade (2005–16) covered in this report showed that, because the new inset flood plain had reached a limiting height, the effects of the large annual flood of 2008 (largest flood since 1978) were relatively small compared to smaller floods in previous decades. Throughout these four decades, the riparian vegetation, which interacts with the river, has undergone a gradual but substantial change that may have lasting effects on the channel morphology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181012","usgsCitation":"Moody, J.A., and Meade, R.H., 2018, Decadal changes in channel morphology of a freely meandering river—Powder River, Montana, 1975–2016: U.S. Geological Survey Open-File Report 2018–1012, 143 p., https://doi.org/10.3133/ofr20181012.","productDescription":"Report: viii, 143 p.; Data Release","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090628","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":352547,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TQ5ZRN","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Channel Cross-section Data for Powder River between Moorhead and Broadus, Montana from 1975 to 2016"},{"id":352545,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1012/coverthb2.jpg"},{"id":352546,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1012/ofr20181012.pdf","text":"Report","size":"35.6 MB"}],"country":"United States","state":"Montana","otherGeospatial":"Powder River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.25,\n 45\n ],\n [\n -106,\n 45\n ],\n [\n -106,\n 45.5\n ],\n [\n -105.25,\n 45.5\n ],\n [\n -105.25,\n 45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"The U.S. Geological Survey (USGS) in cooperation with the city of West Branch and the Herbert Hoover National Historic Site of the National Park Service assessed flood-mitigation scenarios within the West Branch Wapsinonoc Creek watershed. The scenarios are intended to demonstrate several means of decreasing peak streamflows and improving the conveyance of overbank flows from the West Branch Wapsinonoc Creek and its tributary Hoover Creek where they flow through the city and the Herbert Hoover National Historic Site located within the city.
Hydrologic and hydraulic models of the watershed were constructed to assess the flood-mitigation scenarios. To accomplish this, the models used the U.S. Army Corps of Engineers Hydrologic Engineering Center-Hydrologic Modeling System (HEC–HMS) version 4.2 to simulate the amount of runoff and streamflow produced from single rain events. The Hydrologic Engineering Center-River Analysis System (HEC–RAS) version 5.0 was then used to construct an unsteady-state model that may be used for routing streamflows, mapping areas that may be inundated during floods, and simulating the effects of different measures taken to decrease the effects of floods on people and infrastructure.
Both models were calibrated to three historic rainfall events that produced peak streamflows ranging between the 2-year and 10-year flood-frequency recurrence intervals at the USGS streamgage (05464942) on Hoover Creek. The historic rainfall events were calibrated by using data from two USGS streamgages along with surveyed high-water marks from one of the events. The calibrated HEC–HMS model was then used to simulate streamflows from design rainfall events of 24-hour duration ranging from a 20-percent to a 1-percent annual exceedance probability. These simulated streamflows were incorporated into the HEC–RAS model.
The unsteady-state HEC–RAS model was calibrated to represent existing conditions within the watershed. HEC–RAS model simulations with the existing conditions and streamflows from the design rainfall events were then done to serve as a baseline for evaluating flood-mitigation scenarios. After these simulations were completed, three different flood-mitigation scenarios were developed with HEC–RAS: a detention-storage scenario, a conveyance improvement scenario, and a combination of both. In the detention-storage scenario, four in-channel detention structures were placed upstream from the city of West Branch to attenuate peak streamflows. To investigate possible improvements to conveying floodwaters through the city of West Branch, a section of abandoned railroad embankment and an old truss bridge were removed in the model, because these structures were producing backwater areas during flooding events. The third scenario combines the detention and conveyance scenarios so their joint efficiency could be evaluated. The scenarios with the design rainfall events were run in the HEC–RAS model so their flood-mitigation effects could be analyzed across a wide range of flood magnitudes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185002","collaboration":"Prepared in cooperation with the city of West Branch and the National Park Service","usgsCitation":"Cigrand, C.V., 2018, Flood-inundation and flood-mitigation modeling of the West Branch Wapsinonoc Creek Watershed in West Branch, Iowa: U.S. Geological Survey Scientific Investigations Report 2018–5002, 36 p., https://doi.org/10.3133/sir20185002.","productDescription":"viii, 36 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090129","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":352733,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5002/sir20185002.pdf","text":"Report","size":"3.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5002"},{"id":352732,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5002/coverthb.jpg"}],"country":"United States","state":"Iowa","city":"West Branch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.40693664550781,\n 41.64264409952472\n ],\n [\n -91.32488250732422,\n 41.64264409952472\n ],\n [\n -91.32488250732422,\n 41.72289932945416\n ],\n [\n -91.40693664550781,\n 41.72289932945416\n ],\n [\n -91.40693664550781,\n 41.64264409952472\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 S. Clinton Street
Iowa City, IA 52240
Fecal DNA collected noninvasively can provide valuable information about genetic and ecological characteristics. This approach has rarely been used for equids, despite the need for conservation of endangered species and management of abundant feral populations. We examined factors affecting the efficacy of using equid fecal samples for conservation genetics. First, we evaluated two fecal collection methods (paper bag vs. ethanol). Then, we investigated how time since deposition and month of collection impacted microsatellite amplification success and genotyping errors. Between May and November 2014, we collected feral horse fecal samples of known age each month in a feral horse Herd Management Area in western Colorado and documented deterioration in the field with photographs. Samples collected and dried in paper bags had significantly higher amplification rates than those collected and stored in ethanol. There was little difference in the number of loci that amplified per sample between fresh fecal piles and those that had been exposed to the environment for up to 2 months (in samples collected in paper bags). After 2 months of exposure, amplification success declined. When comparing fresh (0–2 months) and old (3–6 months) fecal piles, samples from fresh piles had more matching genotypes across samples, better amplification success and less allelic dropout. Samples defecated during the summer and collected within 2 months of deposition had highest number of genotypes matching among samples, and lowest rates of amplification failure and allelic dropout. Due to the digestive system and amount of fecal material produced by equids, as well as their occurrence in arid ecosystems, we suggest that they are particularly good candidates for noninvasive sampling using fecal DNA.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3956","usgsCitation":"King, S., Schoenecker, K.A., Fike, J.A., and Oyler-McCance, S.J., 2018, Long-term persistence of horse fecal DNA in the environment makes equids particularly good candidates for non-invasive sampling: Ecology and Evolution, v. 8, no. 8, p. 4053-4064, https://doi.org/10.1002/ece3.3956.","productDescription":"12 p.","startPage":"4053","endPage":"4064","ipdsId":"IP-092556","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3956","text":"Publisher Index Page"},{"id":373554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Grand Junction","otherGeospatial":"Little Book Cliffs Wild Horse Herd Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.37051391601562,\n 39.12366825402605\n ],\n [\n -108.28811645507812,\n 39.17478791493289\n ],\n [\n -108.38699340820312,\n 39.28223089949212\n ],\n [\n -108.47763061523438,\n 39.29604824402406\n ],\n [\n -108.51058959960938,\n 39.22480659786848\n ],\n [\n -108.46939086914062,\n 39.16201148082406\n ],\n [\n -108.37051391601562,\n 39.12366825402605\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"King, Sarah R.B.","contributorId":127791,"corporation":false,"usgs":false,"family":"King","given":"Sarah R.B.","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":785637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X schoeneckerk@usgs.gov","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":2001,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn","email":"schoeneckerk@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. 0000-0001-8797-7823 fikej@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":140875,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer","email":"fikej@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785639,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785638,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196198,"text":"70196198 - 2018 - Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands","interactions":[],"lastModifiedDate":"2018-03-26T10:12:45","indexId":"70196198","displayToPublicDate":"2018-03-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands","docAbstract":"Water-limited ecosystems often recover slowly following anthropogenic or natural disturbance. Multitemporal remote sensing can be used to monitor ecosystem recovery after disturbance; however, dryland vegetation cover can be challenging to accurately measure due to sparse cover and spectral confusion between soils and non-photosynthetic vegetation. With the goal of optimizing a monitoring approach for identifying both abrupt and gradual vegetation changes, we evaluated the ability of Landsat-derived spectral variables to characterize surface variability of vegetation cover and bare ground across a range of vegetation community types. Using three year composites of Landsat data, we modeled relationships between spectral information and field data collected at monitoring sites near Canyonlands National Park, UT. We also developed multiple regression models to assess improvement over single variables. We found that for all vegetation types, percent cover bare ground could be accurately modeled with single indices that included a combination of red and shortwave infrared bands, while near infrared-based vegetation indices like NDVI worked best for quantifying tree cover and total live vegetation cover in woodlands. We applied four models to characterize the spatial distribution of putative grassland ecological states across our study area, illustrating how this approach can be implemented to guide dryland ecosystem management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2017.12.008","usgsCitation":"Poitras, T.B., Villarreal, M.L., Waller, E.K., Nauman, T.W., Miller, M.E., and Duniway, M.C., 2018, Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands: Journal of Arid Environments, v. 153, p. 76-87, https://doi.org/10.1016/j.jaridenv.2017.12.008.","productDescription":"12 p.","startPage":"76","endPage":"87","ipdsId":"IP-084812","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468897,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jaridenv.2017.12.008","text":"Publisher Index Page"},{"id":437977,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SWDWLS","text":"USGS data release","linkHelpText":"Grassland State and Transition Map of Canyonlands National Park Needles District and Indian Creek Grazing Allotment"},{"id":352759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.20797729492188,\n 37.81737834565083\n ],\n [\n -109.58862304687499,\n 37.81737834565083\n ],\n [\n -109.58862304687499,\n 38.494443887725055\n ],\n [\n -110.20797729492188,\n 38.494443887725055\n ],\n [\n -110.20797729492188,\n 37.81737834565083\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"153","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6f7e4b0da30c1bfbfe0","contributors":{"authors":[{"text":"Poitras, Travis B. 0000-0001-8677-1743 tpoitras@usgs.gov","orcid":"https://orcid.org/0000-0001-8677-1743","contributorId":195168,"corporation":false,"usgs":true,"family":"Poitras","given":"Travis","email":"tpoitras@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":731644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":731643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waller, Eric K. 0000-0002-9169-9210","orcid":"https://orcid.org/0000-0002-9169-9210","contributorId":203496,"corporation":false,"usgs":true,"family":"Waller","given":"Eric","email":"","middleInitial":"K.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"preferred":true,"id":731645,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731646,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":731648,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731647,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196199,"text":"70196199 - 2018 - Inferring species interactions through joint mark–recapture analysis","interactions":[],"lastModifiedDate":"2018-04-02T13:38:50","indexId":"70196199","displayToPublicDate":"2018-03-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Inferring species interactions through joint mark–recapture analysis","docAbstract":"Introduced species are frequently implicated in declines of native species. In many cases, however, evidence linking introduced species to native declines is weak. Failure to make strong inferences regarding the role of introduced species can hamper attempts to predict population viability and delay effective management responses. For many species, mark–recapture analysis is the more rigorous form of demographic analysis. However, to our knowledge, there are no mark–recapture models that allow for joint modeling of interacting species. Here, we introduce a two‐species mark–recapture population model in which the vital rates (and capture probabilities) of one species are allowed to vary in response to the abundance of the other species. We use a simulation study to explore bias and choose an approach to model selection. We then use the model to investigate species interactions between endangered humpback chub (Gila cypha) and introduced rainbow trout (Oncorhynchus mykiss) in the Colorado River between 2009 and 2016. In particular, we test hypotheses about how two environmental factors (turbidity and temperature), intraspecific density dependence, and rainbow trout abundance are related to survival, growth, and capture of juvenile humpback chub. We also project the long‐term effects of different rainbow trout abundances on adult humpback chub abundances. Our simulation study suggests this approach has minimal bias under potentially challenging circumstances (i.e., low capture probabilities) that characterized our application and that model selection using indicator variables could reliably identify the true generating model even when process error was high. When the model was applied to rainbow trout and humpback chub, we identified negative relationships between rainbow trout abundance and the survival, growth, and capture probability of juvenile humpback chub. Effects on interspecific interactions on survival and capture probability were strongly supported, whereas support for the growth effect was weaker. Environmental factors were also identified to be important and in many cases stronger than interspecific interactions, and there was still substantial unexplained variation in growth and survival rates. The general approach presented here for combining mark–recapture data for two species is applicable in many other systems and could be modified to model abundance of the invader via other modeling approaches.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2166","usgsCitation":"Yackulic, C.B., Korman, J., Yard, M., and Dzul, M.C., 2018, Inferring species interactions through joint mark–recapture analysis: Ecology, v. 99, no. 4, p. 812-821, https://doi.org/10.1002/ecy.2166.","productDescription":"10 p.","startPage":"812","endPage":"821","ipdsId":"IP-086832","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437980,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZC81T9","text":"USGS data release","linkHelpText":"Humpback Chub (Gila cypha) and Rainbow Trout Joint Mark-Recapture Data and Model, Colorado River, Arizona"},{"id":352758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-21","publicationStatus":"PW","scienceBaseUri":"5afee6f7e4b0da30c1bfbfde","contributors":{"authors":[{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Korman, Josh","contributorId":139960,"corporation":false,"usgs":false,"family":"Korman","given":"Josh","email":"","affiliations":[{"id":13333,"text":"Ecometric Research Inc.","active":true,"usgs":false}],"preferred":false,"id":731652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yard, Michael D. 0000-0002-6580-6027 myard@usgs.gov","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":2889,"corporation":false,"usgs":true,"family":"Yard","given":"Michael D.","email":"myard@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":731651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731650,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196192,"text":"70196192 - 2018 - Drivers of solar radiation variability in the McMurdo Dry Valleys, Antarctica","interactions":[],"lastModifiedDate":"2018-04-02T13:38:04","indexId":"70196192","displayToPublicDate":"2018-03-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of solar radiation variability in the McMurdo Dry Valleys, Antarctica","docAbstract":"Annually averaged solar radiation in the McMurdo Dry Valleys, Antarctica has varied by over 20 W m−2 during the past three decades; however, the drivers of this variability are unknown. Because small differences in radiation are important to water availability and ecosystem functioning in polar deserts, determining the causes are important to predictions of future desert processes. We examine the potential drivers of solar variability and systematically eliminate all but stratospheric sulfur dioxide. We argue that increases in stratospheric sulfur dioxide increase stratospheric aerosol optical depth and decrease solar intensity. Because of the polar location of the McMurdo Dry Valleys (77–78°S) and relatively long solar ray path through the stratosphere, terrestrial solar intensity is sensitive to small differences in stratospheric transmissivity. Important sources of sulfur dioxide include natural (wildfires and volcanic eruptions) and anthropogenic emission.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-018-23390-7","usgsCitation":"Obryk, M., Fountain, A.G., Doran, P., Lyons, B., and Eastman, R., 2018, Drivers of solar radiation variability in the McMurdo Dry Valleys, Antarctica: Scientific Reports, v. 8, no. 1, Article number: 5002; 7 p., https://doi.org/10.1038/s41598-018-23390-7.","productDescription":"Article number: 5002; 7 p.","ipdsId":"IP-086694","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468895,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-23390-7","text":"Publisher Index Page"},{"id":352761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":352746,"type":{"id":15,"text":"Index Page"},"url":"https://www.nature.com/articles/s41598-018-23390-7"}],"otherGeospatial":"McMurdo Dry Valleys, Antarctica","volume":"8","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-22","publicationStatus":"PW","scienceBaseUri":"5afee6f8e4b0da30c1bfbfe4","contributors":{"authors":[{"text":"Obryk, Maciej K. 0000-0002-8182-8656","orcid":"https://orcid.org/0000-0002-8182-8656","contributorId":203477,"corporation":false,"usgs":true,"family":"Obryk","given":"Maciej","middleInitial":"K.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":731594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fountain, Andrew G.","contributorId":10410,"corporation":false,"usgs":false,"family":"Fountain","given":"Andrew","email":"","middleInitial":"G.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":731595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doran, Peter","contributorId":203478,"corporation":false,"usgs":false,"family":"Doran","given":"Peter","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":731596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, Berry","contributorId":203479,"corporation":false,"usgs":false,"family":"Lyons","given":"Berry","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":731597,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eastman, Ryan","contributorId":203480,"corporation":false,"usgs":false,"family":"Eastman","given":"Ryan","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":731598,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196208,"text":"70196208 - 2018 - Parasitism and the biodiversity-functioning relationship","interactions":[],"lastModifiedDate":"2018-04-02T13:36:41","indexId":"70196208","displayToPublicDate":"2018-03-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Parasitism and the biodiversity-functioning relationship","docAbstract":"Biodiversity affects ecosystem functioning.
Biodiversity may decrease or increase parasitism.
Parasites impair individual hosts and affect their role in the ecosystem.
Parasitism, in common with competition, facilitation, and predation, could regulate BD-EF relationships.
Parasitism affects host phenotypes, including changes to host morphology, behavior, and physiology, which might increase intra- and interspecific functional diversity.
The effects of parasitism on host abundance and phenotypes, and on interactions between hosts and the remaining community, all have potential to alter community structure and BD-EF relationships.
Global change could facilitate the spread of invasive parasites, and alter the existing dynamics between parasites, communities, and ecosystems.
Species interactions can influence ecosystem functioning by enhancing or suppressing the activities of species that drive ecosystem processes, or by causing changes in biodiversity. However, one important class of species interactions – parasitism – has been little considered in biodiversity and ecosystem functioning (BD-EF) research. Parasites might increase or decrease ecosystem processes by reducing host abundance. Parasites could also increase trait diversity by suppressing dominant species or by increasing within-host trait diversity. These different mechanisms by which parasites might affect ecosystem function pose challenges in predicting their net effects. Nonetheless, given the ubiquity of parasites, we propose that parasite–host interactions should be incorporated into the BD-EF framework.
Accurately quantifying the amount of naturally occurring gas hydrate in marine and permafrost environments is important for assessing its resource potential and understanding the role of gas hydrate in the global carbon cycle. Electrical resistivity well logs are often used to calculate gas hydrate saturations, Sh, using Archie's equation. Archie's equation, in turn, relies on an empirical saturation parameter, n. Though n = 1.9 has been measured for ice‐bearing sands and is widely used within the hydrate community, it is highly questionable if this n value is appropriate for hydrate‐bearing sands. In this work, we calibrate n for hydrate‐bearing sands from the Canadian permafrost gas hydrate research well, Mallik 5L‐38, by establishing an independent downhole Sh profile based on compressional‐wave velocity log data. Using the independently determined Sh profile and colocated electrical resistivity and bulk density logs, Archie's saturation equation is solved for n, and uncertainty is tracked throughout the iterative process. In addition to the Mallik 5L‐38 well, we also apply this method to two marine, coarse‐grained reservoirs from the northern Gulf of Mexico Gas Hydrate Joint Industry Project: Walker Ridge 313‐H and Green Canyon 955‐H. All locations yield similar results, each suggesting n ≈ 2.5 ± 0.5. Thus, for the coarse‐grained hydrate bearing (Sh > 0.4) of greatest interest as potential energy resources, we suggest that n = 2.5 ± 0.5 should be applied in Archie's equation for either marine or permafrost gas hydrate settings if independent estimates of n are not available.
","language":"English","publisher":"AGU","doi":"10.1002/2017JB015138","usgsCitation":"Cook, A.E., and Waite, W., 2018, Archie’s saturation exponent for natural gas hydrate in coarse-grained reservoirs: Journal of Geophysical Research B: Solid Earth, v. 123, no. 3, p. 2069-2089, https://doi.org/10.1002/2017JB015138.","productDescription":"21 p.","startPage":"2069","endPage":"2089","ipdsId":"IP-078323","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468893,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jb015138","text":"Publisher Index Page"},{"id":352757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"3","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-11","publicationStatus":"PW","scienceBaseUri":"5afee6f7e4b0da30c1bfbfdc","contributors":{"authors":[{"text":"Cook, Ann E.","contributorId":18218,"corporation":false,"usgs":true,"family":"Cook","given":"Ann","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":731654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waite, William F. 0000-0002-9436-4109 wwaite@usgs.gov","orcid":"https://orcid.org/0000-0002-9436-4109","contributorId":625,"corporation":false,"usgs":true,"family":"Waite","given":"William F.","email":"wwaite@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":731653,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195781,"text":"sim3389 - 2018 - Geologic map of the Nepenthes Planum Region, Mars","interactions":[],"lastModifiedDate":"2023-03-20T18:10:06.609924","indexId":"sim3389","displayToPublicDate":"2018-03-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3389","title":"Geologic map of the Nepenthes Planum Region, Mars","docAbstract":"This map product contains a map sheet at 1:1,506,000 scale that shows the geology of the Nepenthes Planum region of Mars, which is located between the cratered highlands that dominate the southern hemisphere and the less-cratered sedimentary plains that dominate the northern hemisphere. The map region contains cone- and mound-shaped landforms as well as lobate materials that are morphologically similar to terrestrial igneous or mud vents and flows. This map is part of an informal series of small-scale (large-area) maps aimed at refining current understanding of the geologic units and structures that make up the highland-to-lowland transition zone. The map base consists of a controlled Thermal Emission Imaging System (THEMIS) daytime infrared image mosaic (100 meters per pixel resolution) supplemented by a Mars Orbiter Laser Altimeter (MOLA) digital elevation model (463 meters per pixel resolution). The map includes a Description of Map Units and a Correlation of Map Units that describes and correlates units identified across the entire map region. The geologic map was assembled using ArcGIS software by Environmental Systems Research Institute (http://www.esri.com). The ArcGIS project, geodatabase, base map, and all map components are included online as supplemental data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3389","usgsCitation":"Skinner, J.A., Jr., and Tanaka, K.L., 2018, Geologic map of the Nepenthes Planum Region, Mars: U.S. Geological Survey Scientific Investigations Map 3389, pamphlet 11 p., scale 1:1,506,000, https://doi.org/10.3133/sim3389.","productDescription":"Map: 45.60 x 38.82 inches; Pamphlet: i, 11 p.; Metadata, Spatial Data; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078987","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":437979,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95837GN","text":"USGS data release","linkHelpText":"Interactive Map: USGS SIM 3389 Geologic Map of the Nepenthes Planum Region, Mars"},{"id":352459,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3389/coverthb.jpg"},{"id":352467,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_gis.zip","text":"GIS Files","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3389"},{"id":352463,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_readme.txt","text":"Read Me","size":"4 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3389"},{"id":352462,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_pamphlet.pdf","text":"Pamphlet","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3389"},{"id":352461,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_mapsheet.pdf","text":"Map","size":"74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3389"},{"id":352460,"rank":2,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_geomap_metadata.xml","size":"7 KB","description":"SIM 3389 Metadata"},{"id":400823,"rank":7,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P95837GN","text":"Interactive map","linkHelpText":"- Geologic map of the Nepenthes Planum Region, Mars, 1:1,506,000, Skinner et al. (2018)"}],"contact":"Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
Long before landscape photography became common, artists sketched and painted scenes of faraway places for the masses. Throughout the 19th century, scientific expeditions to Hawaiʻi routinely employed artists to depict images for the people back home who had funded the exploration and for those with an interest in the newly discovered lands.
In Hawaiʻi, artists portrayed the broad variety of people, plant and animal life, and landscapes, but a feature of singular interest was the volcanoes. Painters of early Hawaiian volcano landscapes created art that formed a cohesive body of work known as the “Volcano School” (Forbes, 1992).
Jules Tavernier, Charles Furneaux, and D. Howard Hitchcock were probably the best known artists of this school, and their paintings can be found in galleries around the world. Their dramatic paintings were recognized as fine art but were also strong advertisements for tourists to visit Hawaiʻi.
Many of these masterpieces are preserved in the Museum and Archive Collection of Hawaiʻi Volcanoes National Park, and in this report we have taken the opportunity to match the artwork with the approximate date and volcanological context of the scene.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181027","usgsCitation":"Gaddis, B., and Kauahikaua, J., 2018, Volcano Art at Hawai`i Volcanoes National Park—A Science Perspective: U.S. Geological Survey Open-File Report 2018–1027, 21 p., https://doi.org/10.3133/ofr20181027.","productDescription":"iii, 21 p.","numberOfPages":"27","onlineOnly":"Y","ipdsId":"IP-091723","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":352764,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1027/coverthb.jpg"},{"id":352765,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1027/ofr20181027.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1027"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Hawai`i Volcanoes National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.76690673828125,\n 19.06471383653978\n ],\n [\n -155.0115966796875,\n 19.06471383653978\n ],\n [\n -155.0115966796875,\n 19.64776095569737\n ],\n [\n -155.76690673828125,\n 19.64776095569737\n ],\n [\n -155.76690673828125,\n 19.06471383653978\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"HVO, Volcano Science Center,
Hawaiian Volcano Observatory
U.S. Geological Survey
P.O. Box 51, 1 Crater Rim Road
Hawaiʻi Volcanoes National Park, HI 96718-0051
The volcanic processes that have shaped the Long Valley Caldera in eastern California have also created an abundant supply of natural hot water. This natural resource provides benefits to many users, including power generation at the Casa Diablo Geothermal Plant, warm water for a state fish hatchery, and beautiful scenic areas such as Hot Creek gorge for visitors. However, some features can be dangerous because of sudden and unpredictable changes in the location and flow rate of boiling water. The U.S. Geological Survey monitors several aspects of the hydrothermal system in the Long Valley Caldera including temperature, flow rate, and water chemistry.
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Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025